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The Role of Coopetition in Fostering Innovation and Growth in New Technology-based Firms: A Game Theory Approach

2024· article· en· W4398769248 on OpenAlexaff
Aidin Salamzadeh, Léo‐Paul Dana, Niloofar Rastgoo, Morteza Hadizadeh, S Mortazavi

Bibliographic record

VenueBAR - Brazilian Administration Review · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCoopetitionBusinessIndustrial organizationGame theoryKnowledge managementEconomicsMicroeconomicsComputer science

Abstract

fetched live from OpenAlex

Objective: New technology-based firms (NTBFs) are key actors in creating value through innovation, but they face significant challenges in the rapidly changing and competitive technological environment. Methods: This research is a multi-method analysis aiming to present a model of relationships among drivers for collaboration and competition among technology-based companies and identify effective actions and policies to enhance coopetition (cooperation and competition) that can boost the ability of NTBFs to grow and commercialize innovations. The methodology of this study is exploratory in nature. Thus, it employs literature review method for gathering qualitative data, Fuzzy Delphi method for collecting data from experts, and DEMATEL-ISM method for modeling the relationships among drivers and demonstrating the impact of coopetition on the performance of NTBFs. Results: The research findings show that coopetition can improve growth, innovation, and commercialization in NTBFs by overcoming technological and competitive limitations. Conclusions: The study offers practical and social implications for managers, policy makers, and economic development by highlighting the role of coopetition in fostering innovation and prosperity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.257
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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